Maryland Poverty Line Credit#

Maryland’s Poverty Line Credit provides up to 5% of earned income to eligible Maryland filers with income below the poverty line.

Examples#

Because the Poverty Line Credit is based on the poverty line relative to the Earned Income Tax Credit, which is more generous for families with children and which doesn’t give more for families with more than three children, it primarily reaches low-income childless filers and filers with more than six children.

from policyengine_us import IndividualSim
import pandas as pd
import plotly.express as px


def make(adults, children):
    sim = IndividualSim(year=2022)
    sim.add_person(name="head", age=25, is_tax_unit_head=True)
    members = ["head"]
    if adults > 1:
        sim.add_person(name="spouse", is_tax_unit_head=False)
        members += ["spouse"]
    for i in range(children):
        child = "child{}".format(i)
        sim.add_person(name=child, age=5)
        members += [child]
    sim.add_tax_unit(
        name="tax_unit",
        members=members,
    )
    sim.add_spm_unit(name="spm_unit", members=members)
    sim.add_household(name="household", members=members, state_code="MD")
    sim.vary("employment_income", max=100_000, step=100)
    return pd.DataFrame(
        dict(
            employment_income=sim.calc("employment_income")[0],
            plc=sim.calc("md_poverty_line_credit")[0].round(),
            plc_mtr=-sim.deriv(
                "md_poverty_line_credit",
                "employment_income",
                wrt_target="head",
            ),
            adults=adults,
            children=children,
        )
    )


l = []
for adults in range(1, 3):
    for children in range(0, 10):
        l.append(make(adults, children))

df = pd.concat(l)

LABELS = dict(
    employment_income="Employment income",
    plc="MD Poverty Line Credit",
    plc_mtr="MD Poverty Line Credit marginal tax rate",
    adults="Adults",
    children="Children",
)

fig = px.line(
    df,
    "employment_income",
    "plc",
    color="children",
    animation_frame="adults",
    labels=LABELS,
    title="Maryland Poverty Line Credit",
)
fig.update_layout(
    xaxis_tickformat="$,",
    yaxis_tickformat="$,",
    yaxis_range=[0, df.plc.max() * 1.05],
)
fig.show()

Maryland’s Poverty Line Credit creates marginal tax rates as low as -15.3%, and then infinite marginal tax rates at its ineligibility cliff (100% of the poverty line).

fig = px.line(
    df,
    "employment_income",
    "plc_mtr",
    color="children",
    animation_frame="adults",
    labels=LABELS,
    title="Maryland Poverty line credit marginal tax rate",
)
fig.update_layout(
    xaxis_tickformat="$,", yaxis_tickformat=".1%", yaxis_range=[-0.2, 0.2]
)
fig.show()

Budgetary impact#

Applying 2022 rules to the 2020 Current Population Survey, OpenFisca US estimates that the Maryland Poverty Line Credit costs $17 million.

from policyengine_us import Microsimulation

sim = Microsimulation(dataset_year=2020)

sim.calc("md_poverty_line_credit", period=2022).sum() / 1e6
---------------------------------------------------------------------------
FileNotFoundError                         Traceback (most recent call last)
File /opt/hostedtoolcache/Python/3.9.16/x64/lib/python3.9/site-packages/policyengine_core/simulations/simulation.py:182, in Simulation.build_from_dataset(self)
    181 try:
--> 182     data = self.dataset.load(self.dataset_year)
    183 except:

File /opt/hostedtoolcache/Python/3.9.16/x64/lib/python3.9/site-packages/policyengine_core/data/dataset.py:126, in Dataset.load(self, year, key, mode)
    124 if key is None:
    125     # If no key provided, return the basic H5 reader.
--> 126     return h5py.File(file, mode=mode)
    127 else:
    128     # If key provided, return only the values requested.

File /opt/hostedtoolcache/Python/3.9.16/x64/lib/python3.9/site-packages/h5py/_hl/files.py:567, in File.__init__(self, name, mode, driver, libver, userblock_size, swmr, rdcc_nslots, rdcc_nbytes, rdcc_w0, track_order, fs_strategy, fs_persist, fs_threshold, fs_page_size, page_buf_size, min_meta_keep, min_raw_keep, locking, alignment_threshold, alignment_interval, meta_block_size, **kwds)
    564     fcpl = make_fcpl(track_order=track_order, fs_strategy=fs_strategy,
    565                      fs_persist=fs_persist, fs_threshold=fs_threshold,
    566                      fs_page_size=fs_page_size)
--> 567     fid = make_fid(name, mode, userblock_size, fapl, fcpl, swmr=swmr)
    569 if isinstance(libver, tuple):

File /opt/hostedtoolcache/Python/3.9.16/x64/lib/python3.9/site-packages/h5py/_hl/files.py:231, in make_fid(name, mode, userblock_size, fapl, fcpl, swmr)
    230         flags |= h5f.ACC_SWMR_READ
--> 231     fid = h5f.open(name, flags, fapl=fapl)
    232 elif mode == 'r+':

File h5py/_objects.pyx:54, in h5py._objects.with_phil.wrapper()

File h5py/_objects.pyx:55, in h5py._objects.with_phil.wrapper()

File h5py/h5f.pyx:106, in h5py.h5f.open()

FileNotFoundError: [Errno 2] Unable to open file (unable to open file: name = '/home/runner/work/policyengine-us/policyengine-us/policyengine_us/data/storage/cps_2020.h5', errno = 2, error message = 'No such file or directory', flags = 0, o_flags = 0)

During handling of the above exception, another exception occurred:

TypeError                                 Traceback (most recent call last)
Cell In[3], line 3
      1 from policyengine_us import Microsimulation
----> 3 sim = Microsimulation(dataset_year=2020)
      5 sim.calc("md_poverty_line_credit", period=2022).sum() / 1e6

File /opt/hostedtoolcache/Python/3.9.16/x64/lib/python3.9/site-packages/policyengine_core/simulations/simulation.py:131, in Simulation.__init__(self, tax_benefit_system, populations, situation, dataset, dataset_year, reform)
    129     self.dataset = dataset
    130     self.dataset_year = dataset_year
--> 131     self.build_from_dataset()
    133 # Backwards compatibility methods
    134 self.calc = self.calculate

File /opt/hostedtoolcache/Python/3.9.16/x64/lib/python3.9/site-packages/policyengine_core/simulations/simulation.py:184, in Simulation.build_from_dataset(self)
    182         data = self.dataset.load(self.dataset_year)
    183     except:
--> 184         data = self.dataset.load()
    185 except FileNotFoundError as e:
    186     raise FileNotFoundError(
    187         f"The dataset file {self.dataset.name} (with year {self.dataset_year}) could not be found. "
    188         + "Make sure you have downloaded or built it using the `policyengine-core data` command."
    189     ) from e

TypeError: load() missing 1 required positional argument: 'year'